Muhannad Ismael

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This paper proposes a novel stereovision framework for multi-view 3D reconstruction relying on inputs of both several sets of multi-baseline views and a visual hull [3]. The pipeline is illustrated in figure 1. Our Contributions of this paper are threefold: (i) improvement of our multi-baseline stereovision method [2] by VH guidance, (ii) carving VH from(More)
This chapter concentrates on dense image correspondence estimation with a special focus on stereo. Images are the basic input for a vast majority of algorithms dealing with the reconstruction of the real world. To analyze a scene from a collection of images it becomes inevitable to put these images into correspondence. These correspondences then form the(More)
This paper proposes a novel framework for multi-baseline stereovision exploiting the information redundancy to deal with known problems related to occluded regions. Inputs are multiple images shot or rectified in simplified geometry which induces a convenient sampling scheme of scene space: the disparity space. Instead of uniquely relying on image-space(More)
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